The initial calls to the loaded TorchScript model take extremely long (even 1000x longer than the non-jit run, 20s vs 0.02s). I understand that some "optimizations" happen under the hood, but this is really broken user experience for a number of reasons:
torch.jit.optimized_execution(False)
not mentioned in docsLoad TorchScript model, run with variable-sized input. Notice extremely slow initial runtimes.
Expected behaviorOptimisation is fast or does not happen implicitly when calling the model. Optimisation not re-run for inputs of different shape. Clear documentation.
EnvironmentPyTorch version: 1.9.0.dev20210501+cu111
Is debug build: False
CUDA used to build PyTorch: 11.1
ROCM used to build PyTorch: N/A
OS: Ubuntu 20.04.2 LTS (x86_64)
GCC version: (Ubuntu 9.3.0-17ubuntu1~20.04) 9.3.0
Clang version: Could not collect
CMake version: version 3.16.3
Python version: 3.8 (64-bit runtime)
Is CUDA available: True
CUDA runtime version: Could not collect
GPU models and configuration: GPU 0: NVIDIA GeForce RTX 3090
Nvidia driver version: 465.19.01
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Versions of relevant libraries:
[pip3] numpy==1.19.4
[pip3] pytorch-lightning==1.2.10
[pip3] pytorch-lightning-bolts==0.3.0
[pip3] torch==1.9.0.dev20210501+cu111
[pip3] torch-stft==0.1.4
[pip3] torchaudio==0.9.0.dev20210501
[pip3] torchext==0.0.6
[pip3] torchmetrics==0.2.0
[pip3] torchtext==0.10.0.dev20210501
[pip3] torchvision==0.10.0.dev20210501+cu111
[conda] Could not collect
cc @gmagogsfm
jayakommurude-vri-es, wangyunxiaa and wolegechu
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